Run: 2026-07-25-01KYCTJR5MY7N6MW75SCA88421

Run Details

Duration:
2.5s
Cost:
$0.001363
Provider:
Google AI Studio

Model input

System
You are an expert fiction writer. Always keep the following rules in mind: - Write in past tense and use General English spelling, grammar, and colloquialisms/slang. - Write in active voice - Always follow the "show, don't tell" principle. - Avoid adverbs and cliches and overused/commonly used phrases. Aim for fresh and original descriptions. - Convey events and story through dialogue. - Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. - Skip "he/she said said" dialogue tags and convey people's actions or face expressions through their speech - Avoid mushy dialog and descriptions, have dialogue always continue the action, never stall or add unnecessary fluff. Vary the descriptions to not repeat yourself. - Put dialogue on its own paragraph to separate scene and action. - Reduce indicators of uncertainty like "trying" or "maybe" When writing text: - NEVER conclude the scene on your own, follow the beat instructions very closely. - NEVER end with foreshadowing. - NEVER write further than what I prompt you with. - AVOID imagining possible endings, NEVER deviate from the instructions. - STOP EARLY if the continuation contains what was required in the instructions. You do not need to fill out the full amount of words possible.
User/Human
Take into account the following glossary of characters/locations/items/lore... when writing your response: <codex> <character id="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary. </instructions>

Model response

AI
Water hissed against hot asphalt. Detective Harlow Quinn tracked the target past the green neon sign of The Raven's Nest, boots pounding the slick pavement with military precision. Salt-and-pepper hair plastered to her skull. Rain dripped from her sharp jawline. The leather watch on her left wrist ticked past midnight. Tomás Herrera vaulted over a cast-iron trash bin ahead, his curly dark hair bouncing under the streetlamps. Quinn closed the distance. The suspect cut down an alleyway reeking of stale ale and rotting masonry. Brick walls closed in. Tomás scrambled over a rusted chain-link fence bordering the abandoned Camden Tube station. Quinn hauled herself over the barbed wire, tearing her raincoat. Metal screeched. She dropped hard onto concrete steps descending into pitch blackness. Stale subterranean air rushed up, carrying the metallic scent of copper and old dust. A hand-carved bone token clattered on the floor three steps down. Quinn snatched it. The surface was warm, humming with a vibration that set her teeth on edge. Shadows swallowed the tunnel below. Murmurs drifted up from the platform, sounding too loud, too numerous for an abandoned station. Footsteps squelched through puddles deeper in the dark. Quinn thumbed the safety off her service pistol. The tunnel opened into the Veil Market. Bioluminescent moss clung to the curved brick ceiling, casting an emerald glow over rows of makeshift stalls. Vendors draped in heavy wool cloaks hovered over crates of glass phials and obsidian blades. Nobody looked up as Tomás melted into the crowd of pale-faced figures and horned silhouettes. Quinn stepped past a merchant boiling teeth in a brass kettle. The heat choked her throat. A heavy iron gate stood twenty paces ahead, marking the boundary of the deeper tunnels where the market bled into absolute black. Tomás slipped between the bars. Quinn stopped at the threshold. The air beyond the gate tasted like ozone and dried blood. She gripped the cold iron, her knuckles turning white.
created_at"2026-07-25T14:24:02.242Z" 7/25/2026, 2:24:02 PM
model"google/gemini-3.5-flash-lite-20260721"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency251
moderation_latency(null)
generation_time2474
tokens_prompt1104
tokens_completion512
native_tokens_prompt1042
native_tokens_completion420
native_tokens_completion_images0
native_tokens_reasoning0
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"STOP"
service_tier"default"
usage0.0013626
router(null)
provider_responses
0
endpoint_id"6bd8f433-79e1-416c-b407-1772eb796c9a"
id"AsdkaoWyEufQ-8YPy8Tm-Ak"
is_byokfalse
latency251
model_permaslug"google/gemini-3.5-flash-lite-20260721"
provider_name"Google AI Studio"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1784989442-ms1qWde5hLGHMcIXVzJx"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1784989442-O7Mbx2mKYnYvBkBJpGbl"
upstream_id"AsdkaoWyEufQ-8YPy8Tm-Ak"
total_cost0.0013626
cache_discount(null)
upstream_inference_cost0
provider_name"Google AI Studio"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount323
totalAiIsmAdverbs0
found(empty)
highlights(empty)
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
69.04% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount323
totalAiIsms2
found
0
word"pounding"
count1
1
word"footsteps"
count1
highlights
0"pounding"
1"footsteps"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences32
matches(empty)
98.21% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences32
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences32
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen23
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords323
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
41.64% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions19
wordCount323
uniqueNames10
maxNameDensity2.17
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Harlow1
Quinn7
Raven1
Nest1
Herrera1
Camden1
Tube1
Veil1
Market1
Tomás4
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Herrera"
4"Market"
5"Tomás"
places
0"Veil"
globalScore0.416
windowScore0.833
41.30% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences23
glossingSentenceCount1
matches
0"tasted like ozone and dried blood"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount323
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences32
matches(empty)
78.79% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs8
mean40.38
std17.19
cv0.426
sampleLengths
067
134
236
311
445
562
643
725
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences32
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs51
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences32
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount329
adjectiveStacks0
stackExamples(empty)
adverbCount3
adverbRatio0.00911854103343465
lyAdverbCount1
lyAdverbRatio0.00303951367781155
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences32
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences32
mean10.09
std5.3
cv0.525
sampleLengths
05
123
26
36
410
517
64
713
84
913
1010
112
1210
1314
1411
153
1614
175
1815
198
208
217
2217
2315
2415
2511
265
2722
285
295
3011
319
93.75% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats0
diversityRatio0.5625
totalSentences32
uniqueOpeners18
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences31
matches(empty)
ratio0
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount2
totalSentences31
matches
0"She dropped hard onto concrete"
1"She gripped the cold iron,"
ratio0.065
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount30
totalSentences31
matches
0"Water hissed against hot asphalt."
1"Detective Harlow Quinn tracked the"
2"Salt-and-pepper hair plastered to her"
3"Rain dripped from her sharp"
4"The leather watch on her"
5"Tomás Herrera vaulted over a"
6"Quinn closed the distance."
7"The suspect cut down an"
8"Brick walls closed in."
9"Tomás scrambled over a rusted"
10"Quinn hauled herself over the"
11"She dropped hard onto concrete"
12"A hand-carved bone token clattered"
13"Quinn snatched it."
14"The surface was warm, humming"
15"Shadows swallowed the tunnel below."
16"Murmurs drifted up from the"
17"Footsteps squelched through puddles deeper"
18"Quinn thumbed the safety off"
19"The tunnel opened into the"
ratio0.968
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences31
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences17
technicalSentenceCount1
matches
0"The surface was warm, humming with a vibration that set her teeth on edge."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
84.0912%